AI and Audio: Implications as the Technology Moves Into the Broadcast Soundscape Audio execs see artificial intelligence as an ultra-smart, ultra-fast assistant By Dan Daley, Audio Editor Wednesday, January 15, 2025 - 7:00 am
Print This Story | Subscribe
Story Highlights
Artificial intelligence (AI) already has significant presence in professional audio. It's automating and streamlining such tasks as editing, mixing, mastering, and, increasingly, music creation and generation. It allows producers and engineers to work faster and more efficiently and offers new creative possibilities. Even so, there are concerns regarding the potential for loss of human creative input and the ethical implications of AI-generated content.
SVG asked some industry thought leaders for their views on this inflective moment in pro audio's evolution.
NBC Sports' Karl Malone: The beauty of AI lies in its ability to analyze a scenario and evaluate far more parameters of an audio signal than we ever could as humans.
Karl Malone, senior director, audio engineering, NBC Sports:
I'm excited to have the ability to see what can be achieved with new AI tools in broadcast audio. We already look to Cedars, Isotopes, and upmix engines to look after complex tasks, and the use of Kick for mixing ball effects in European football should be enough for us to take automated and intelligent technology seriously.
The beauty of AI lies in its ability to analyze a scenario and evaluate far more parameters of an audio signal than we ever could as humans. Although A1s excel at brain-to-hand-to-eye coordination, we simply cannot match the computational foresight of AI. It can process information in real time, anticipate outcomes, and make decisions or offer suggestions based on both its analysis and the specific training it has received for a given situation.
However, the artistic nuances and creative expertise that define an A1's work are irreplaceable, making AI unsuitable for mixing a major broadcast show on its own. That said, AI could be highly effective in handling secondary outputs, such as creating a dedicated mix for second-screen feeds - focusing, for instance, on mixing close ball effects and radio commentary as a separate audio feed.
AI can also be helpful in the QC of large numbers of program feeds to be able to check audio and video for all sorts of visual- and audio-mix issues: out-of-sync audio and video, artifacts in video-resolution-quality fluctuations, missing audio, clipping, metadata timing, phase, etc. It can alert the MCR/BOC operator to take a closer look or listen.
Ultimately, we decide if we want to use it in these early stages or not, so it's not being forced upon anyone to implement.
Audio-Technica's Gary Dixon: AI is a tool for humans to better react to unpredictable events caused by interesting human nature.
Gary Dixon, director, broadcast and production business development, Audio-Technica:
Audio is dynamic, and the moments worth hearing are typically unpredictable: such as a crash in racing, the eruption of the crowd at the 18th hole, or holding a music note just a little longer at a concert. AI in professional audio and in microphones specifically will be used as a tool for quickly adapting hardware in unpredictable audio situations. Hardware can have limitations in gain structure, dynamics, and general EQ, whereas AI can assist the human in reacting to these situations.
However, for audio to appeal to humans, the final monitoring stage and final adjustments will need to be done by humans. AI is a tool for humans to better react to unpredictable events caused by interesting human nature.
Christian Scheck, head of marketing content, Lawo:
From a content-creation perspective, generative AI is proving extremely powerful. As far as video is concerned, it is already possible to feed a generative AI engine with some information to get usable footage.
Similarly, on the audio side, music written and performed by AI engines is beginning to scare songwriters and performers alike, while artificially generated voiceovers for videos and live commentary for broadcasts manage to fool a growing number of listeners into believing that they are listening to a human.
AI has been used to good effect for the generation of closed captioning, which used to be a time-consuming task and can now be prepared within minutes. Results, however, still need to be checked by a human for consistency, tone of voice, and, critically, accuracy.
Lawo's Christian Scheck: AI has been used to good effect for the generation of closed captioning, which used to be a time-consuming task. Results, however, still need to be checked by a human.
In the broadcast industry, more-advanced algorithms [can] help audio engineers, for instance, cope with a rapidly growing workload, not least in immersive-audio-mixing scenarios that require the supervision and delivery of several presentations and downmix formats - all from one console and by a single A1.
Ultimately, the success of AI in live-production scenarios will depend on how well it responds to unexpected situations. It may very well become a powerful assistant that complements media production based on the use of Lawo solutions, but whether it will be able to replace DSP audio or high-quality video processing remains to be seen.
AI can add value in other ways. On a modern, software-based platform like HOME Apps, for instance, AI can streamline process monitoring, vastly improve debug times, and shorten downtimes, as well as assist with data analysis and help predict failure conditions.
Other applications could include advanced auto-mixing algorithms or the intelligent deployment of apps and services to max out hardware and software utilization in scenarios with a limited number of computing resources.
However, AI needs to be applied wi
